Li Yuan-pei, Li Lin-han, He Ming-zhen, Zhao Fei, He Zhong, Wan Wei, Li Jun-xiang, Jiang Jie, Zhou Yi-biao, Jiang Qing-wu
Department of Epidemiology, Fudan University, Shanghai, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2011 Jun;32(6):583-6.
To detect the snail habitats from the marshland of Eastern Dongting Lake Area, using the Remote Sensing (RS) and Geographic Information System (GIS) technology based on the China-Brazil Earth Resources Satellite-02B (CBERS-02B) CCD images.
According to the two typical traits of snail habitats in marshland including "water in summer and land in winter" and "no grass, no snails", the "water in summer and land in winter" region and the vegetation coverage region were calculated by RS image processing respectively. The two regions mentioned above were then overlapped to confirm the snail habitats through comparing with the data from field survey under spatial overlapping of Arcgis as the last step.
In Eastern Dongting Lake area, the "water in summer and land in winter" region and vegetation coverage region were predicted based on the formula normalized difference water index (NDWI) > 0.01 and normalized difference vegetation index (NDVI) > 0.36, respectively. The snail habitat was determined by theme overlay of the two regions said above. The agreement rate between the prediction and the geospatial data of field survey was 93.55%, which demonstrated the final results were credible and reliable.
CBERS-02B image could be used to detect the snail habitats and to monitor the changes of them, so as to find out the characteristics of distribution and the trends of diffusion. The snail index (discriminant 1 and 2) seemed to be suitable for the detection of snail habitats in the marshland of Lake area and used for the programs of snail control.
利用基于中巴地球资源卫星02B星（CBERS-02B）电荷耦合器件（CCD）影像的遥感（RS）和地理信息系统（GIS）技术，探测东洞庭湖地区湿地的钉螺孳生地。
根据湿地钉螺孳生地“夏水冬陆”和“无草不成螺”这两个典型特征，分别通过RS图像处理计算出“夏水冬陆”区域和植被覆盖区域。最后，将上述两个区域进行叠加，并在ArcGIS空间叠加的基础上与实地调查数据进行比较，以确定钉螺孳生地。
在东洞庭湖地区，分别基于归一化差异水体指数（NDWI）>0.01和归一化差异植被指数（NDVI）>0.36的公式预测出“夏水冬陆”区域和植被覆盖区域。通过上述两个区域进行专题叠加确定钉螺孳生地。预测结果与实地调查地理空间数据的符合率为93.55%，表明最终结果可信可靠。
CBERS-02B影像可用于探测钉螺孳生地及其变化情况，从而了解其分布特征和扩散趋势。钉螺指数（判别式1和2）似乎适用于湖区湿地钉螺孳生地的探测，并可用于钉螺防治工作。
